30:[{"id":"7e24f184023fb97d750f044e83e836e362244a97c449bd28b7f936c016813033840cbc8d2dd3c2c5ebe0691021ef0d2a56072dd44adb83010913bfa72802d9c6","href":"https://static.observableusercontent.com/files/7e24f184023fb97d750f044e83e836e362244a97c449bd28b7f936c016813033840cbc8d2dd3c2c5ebe0691021ef0d2a56072dd44adb83010913bfa72802d9c6","name":"bv_template.csv","type":"text/csv","lastModified":1634294942542.797,"size":3507},{"id":"d46979989b315b5f2e122f036438aec59c106ce118d6274d1d6d8d44ecd8234d4b415ce64aaca1dff4ef1392c242df0591a908e4d5000eabd6978a663e652cde","href":"https://static.observableusercontent.com/files/d46979989b315b5f2e122f036438aec59c106ce118d6274d1d6d8d44ecd8234d4b415ce64aaca1dff4ef1392c242df0591a908e4d5000eabd6978a663e652cde","name":"perf@2.csv","type":"text/csv","lastModified":1634307527672.119,"size":569},{"id":"8407197d751395e3c5449bec1b42465bab2164c36401f7419c10decfb12ee29320151837e9ef8f1d1d5345e647e5537236d9647a878e3309ed97841a6619de21","href":"https://static.observableusercontent.com/files/8407197d751395e3c5449bec1b42465bab2164c36401f7419c10decfb12ee29320151837e9ef8f1d1d5345e647e5537236d9647a878e3309ed97841a6619de21","name":"bv_template@1.csv","type":"text/csv","lastModified":1634395899054.788,"size":3766},{"id":"0f87527bc85243ae7c8266eba1fa8ae589963d8783b8e835557b60a414b388728abfd796f6b6de2b2b25960f71367419d28bb850f739f3b29e79fd4650f2aad0","href":"https://static.observableusercontent.com/files/0f87527bc85243ae7c8266eba1fa8ae589963d8783b8e835557b60a414b388728abfd796f6b6de2b2b25960f71367419d28bb850f739f3b29e79fd4650f2aad0","name":"perf@6.csv","type":"text/csv","lastModified":1634566883391.974,"size":565},{"id":"ccea945e9d8df409299ca1cd2e795b874a9435ce06669111ecedd181aac64ab26d796cac661a412f39b387585a72b7286977414e5d9254afcb5492a3e0795d6d","href":"https://static.observableusercontent.com/files/ccea945e9d8df409299ca1cd2e795b874a9435ce06669111ecedd181aac64ab26d796cac661a412f39b387585a72b7286977414e5d9254afcb5492a3e0795d6d","name":"gp_usa_sp_pcs@1.json","type":"application/json","lastModified":1635348041573.707,"size":6312},{"id":"5c8e6cc68669d8dd4be73db793f5b38ae121bfa3c5d7bf01dbb3b6400f026c66225cd4114a0e17b0fb1ea88d3565822eafd23087c36085c01b0ebd1b38c7228a","href":"https://static.observableusercontent.com/files/5c8e6cc68669d8dd4be73db793f5b38ae121bfa3c5d7bf01dbb3b6400f026c66225cd4114a0e17b0fb1ea88d3565822eafd23087c36085c01b0ebd1b38c7228a","name":"gp_usa_2021_sp_elements.json","type":"application/json","lastModified":1635596649028.897,"size":22345},{"id":"e4644316f5c501e61fd2408dc3f492bc4739d18957ccdc6e961dc49792ea7335982542a8803b30aab5323f83443cfc8ddb4c663a7ee177edaa230dbc5df002d5","href":"https://static.observableusercontent.com/files/e4644316f5c501e61fd2408dc3f492bc4739d18957ccdc6e961dc49792ea7335982542a8803b30aab5323f83443cfc8ddb4c663a7ee177edaa230dbc5df002d5","name":"gp_usa_sp_pcs.json","type":"application/json","lastModified":1635035972831.975,"size":6454},{"id":"97aa03b7492ff95e79d29d9b72e1efaf767744f8b01873eb1ccc0ab30cfc5d27bec99a9487ff8ec80e27b857d13ec8ecbf53fee3a2a0d24c76fc17a6293cfe69","href":"https://static.observableusercontent.com/files/97aa03b7492ff95e79d29d9b72e1efaf767744f8b01873eb1ccc0ab30cfc5d27bec99a9487ff8ec80e27b857d13ec8ecbf53fee3a2a0d24c76fc17a6293cfe69","name":"tes.csv","type":"text/csv","lastModified":1635036416254.594,"size":3864},{"id":"4cdb66b5391128f51807615eef5a43bb372969e786ce823d787bff76a9c53c2ca6a0b77969dd927fbf2f2ae8ba382e3db3c6f62b677f522d527a4577229c3a68","href":"https://static.observableusercontent.com/files/4cdb66b5391128f51807615eef5a43bb372969e786ce823d787bff76a9c53c2ca6a0b77969dd927fbf2f2ae8ba382e3db3c6f62b677f522d527a4577229c3a68","name":"tss.csv","type":"text/csv","lastModified":1635037118651.489,"size":580}] 2e:{"title":"SP Skate America","cells":[{"id":0,"value":"# SP Skate America","pinned":false,"hidden":false,"mode":"md"},{"id":887,"value":"### ISU Grand Prix of Figure Skating 2021: Women","pinned":false,"hidden":false,"mode":"md"},{"id":832,"value":"\n

Best viewed in desktop and mobile horizontal version, but we’re working on mobile vertical too!\n

","pinned":false,"hidden":false,"mode":"md"},{"id":186,"value":"### Trusova in lead after SP even after ditching 3A","pinned":false,"hidden":false,"mode":"md"},{"id":200,"value":"
\n $\"ScAm\"$ \n
","pinned":false,"hidden":false,"mode":"html"},{"id":80,"value":"## Total Segment Score","pinned":false,"hidden":false,"mode":"md"},{"id":423,"value":"The headers of the table are clickable! Click one one to explore who is better in elements versus components.","pinned":false,"hidden":false,"mode":"md"},{"id":723,"value":"Inputs.table(perf, {\n format: {\n Total_Segment_Score: sparkbar(d3.max(perf, d => d.Total_Segment_Score)),\n Total_Element_Score: sparkbar(d3.max(perf, d => d.Total_Element_Score)),\n Program_Component_Score: sparkbar(d3.max(perf, d => d.Program_Component_Score)),\n Nation: flag\n}})","pinned":false,"hidden":false,"mode":"ojs"},{"id":642,"value":"
Visualizing Open-Source Code, Contributions & Communities
","pinned":false,"hidden":false,"mode":"html"},{"id":56,"value":"## Total Element Score","pinned":false,"hidden":false,"mode":"md"},{"id":129,"value":"**How to read the chart:**
\n- Each chart represents elements of the skater's program in the order they were performed.
\n- The charts are sorted by the skater's ranking in the program.
\n- The line chart stands for the final score of the elements performed; hovering over the line chart, you can see the name of the element and its score.
\n- The area chart represents the range of the maximum and minimum possible score in accordance with the GOE (Grade of Execution).","pinned":false,"hidden":false,"mode":"md"},{"id":47,"value":"tesChart(tesData, names, 29)","pinned":false,"hidden":false,"mode":"ojs"},{"id":485,"value":"
Special marks in the element's name:
\n< - jump had less than a ½ turn but more than a ¼ turn completed on the ice, reducing the base value to 70% of its original value
\nq - jump landed on the quarter
\n * - elements nullified
\n
","pinned":false,"hidden":false,"mode":"html"},{"id":648,"value":"
Visualizing Open-Source Code, Contributions & Communities
","pinned":false,"hidden":false,"mode":"html"},{"id":66,"value":"## Program Component Score","pinned":false,"hidden":false,"mode":"md"},{"id":501,"value":"**How to read the chart:**
\n- Each axis is a component under Performance Component Score. The skater's score for that program component is indicated by their position on the axis. The further the point is from the center, the higher the score.\n- Each line corresponds to a skater. Hover or click on the line to focus on that skater. You can hover on the legend too to do the same thing.\n- Skaters with a high PCS tend to have larger circle sizes. We've chosen a non-zero starting point to better visualize the small decimal point differences between skaters that might make or break a program.\n- __[UPCOMING] We'll be adding PCS totals in a future.__","pinned":false,"hidden":false,"mode":"md"},{"id":754,"value":"chart(data, names, pcsTotal, 6.5, 9)","pinned":false,"hidden":false,"mode":"ojs"},{"id":655,"value":"
Visualizing Open-Source Code, Contributions & Communities
","pinned":false,"hidden":false,"mode":"html"},{"id":239,"value":"Will be happy to see your comments 😃","pinned":false,"hidden":false,"mode":"md"},{"id":585,"value":"
Special thanks for tips and tricks with coding to @Mike Bostock, @Fabian Iwand,
\n
@Brett Cooper and @Duane Millar Barlow and Adam Gsellman for design advice
","pinned":false,"hidden":false,"mode":"html"},{"id":382,"value":"
Visualizing Open-Source Code, Contributions & Communities
\n
@Bianchi Dy & @Dmitry Si
\n
Data Vis Enthusiasts, with the help of Observable
","pinned":false,"hidden":false,"mode":"html"},{"id":627,"value":"
Visualizing Open-Source Code, Contributions & Communities
","pinned":false,"hidden":false,"mode":"html"},{"id":854,"value":"
Technical info\n
","pinned":false,"hidden":false,"mode":"md"},{"id":137,"value":"function sparkbar(max) {\n return x => htl.html`
${x.toLocaleString(\"en\")}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":739,"value":"import {chart} from \"@bianchi-dy/radar-chart\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":962,"value":"import {tesChart} from \"@amidsi/vega-lite_facets\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":766,"value":"pcsData = FileAttachment(\"gp_usa_sp_pcs@1.json\").json();","pinned":false,"hidden":false,"mode":"ojs"},{"id":778,"value":"names = pcsData.names","pinned":false,"hidden":false,"mode":"ojs"},{"id":775,"value":"data = pcsData.pcs","pinned":false,"hidden":false,"mode":"ojs"},{"id":784,"value":"pcsTotal = pcsData.pcs_total","pinned":false,"hidden":false,"mode":"ojs"},{"id":548,"value":"import {isoAlpha3toEmoji} from \"@mbostock/iso-3166-alpha\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":725,"value":"flag = code => html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"// bv1= (await FileAttachment(\"bv_template@1.csv\").csv()).map(d => ({...d, place: +d.place}))\nbv1=d3.csvParse(await FileAttachment(\"tes.csv\").text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs"},{"id":89,"value":"bv2 = {\n for (let i=0; i< bv1.length; i+=1) {\n console.log(i);\n bv1[i]['desc_sop'] = bv1[i]['aspect_desc'] + '/\\n' + bv1[i]['SOP']\n } \n return bv1\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":139,"value":"perf=d3.csvParse(await FileAttachment(\"tss.csv\").text(), d3.autoType)","pinned":false,"hidden":false,"mode":"ojs"},{"id":980,"value":"tesData =tesData_raw.tes","pinned":false,"hidden":false,"mode":"ojs"},{"id":984,"value":"tesData_raw=FileAttachment(\"gp_usa_2021_sp_elements.json\").json()","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W30","stdlib":"1","titling":"auto"}